Overview

Dataset statistics

Number of variables7
Number of observations159
Missing cells3
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.1 KiB
Average record size in memory58.8 B

Variable types

Categorical1
Text3
Numeric2
DateTime1

Dataset

Description부산광역시 노인교실 현황에 대한 데이터로 구군명, 노인교실명, 도로명주소, 전화번호, 경도, 위도, 데이터기준일자에 항목에 대한 정보를 제공합니다.
Author부산광역시
URLhttps://www.data.go.kr/data/15065862/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
경도 is highly overall correlated with 구군명High correlation
위도 is highly overall correlated with 구군명High correlation
구군명 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
전화번호 has 3 (1.9%) missing valuesMissing
노인교실명 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:10:33.912571
Analysis finished2023-12-12 12:10:35.117886
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구군명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
북구
19 
해운대구
18 
부산진구
16 
금정구
14 
동래구
13 
Other values (11)
79 

Length

Max length4
Median length3
Mean length2.9433962
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row중구
2nd row서구
3rd row서구
4th row서구
5th row서구

Common Values

ValueCountFrequency (%)
북구 19
11.9%
해운대구 18
11.3%
부산진구 16
10.1%
금정구 14
8.8%
동래구 13
8.2%
남구 13
8.2%
영도구 12
7.5%
연제구 11
6.9%
사상구 10
 
6.3%
사하구 8
 
5.0%
Other values (6) 25
15.7%

Length

2023-12-12T21:10:35.194142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
북구 19
11.9%
해운대구 18
11.3%
부산진구 16
10.1%
금정구 14
8.8%
동래구 13
8.2%
남구 13
8.2%
영도구 12
7.5%
연제구 11
6.9%
사상구 10
 
6.3%
사하구 8
 
5.0%
Other values (6) 25
15.7%

노인교실명
Text

UNIQUE 

Distinct159
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-12T21:10:35.432735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length9.8742138
Min length5

Characters and Unicode

Total characters1570
Distinct characters187
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)100.0%

Sample

1st row대한노인회 부산중구지회 부설 노인대학
2nd row노인건강학교
3rd row소문노인대학
4th row한마음노인대학
5th row해강노인교실
ValueCountFrequency (%)
노인대학 17
 
7.0%
노인교실 13
 
5.3%
부설 8
 
3.3%
대한노인회 7
 
2.9%
부설노인대학 3
 
1.2%
부설노인교실 3
 
1.2%
늘푸른대학 3
 
1.2%
사하구종합사회복지관 1
 
0.4%
사하복지노인교실 1
 
0.4%
몰운대종합사회복지관 1
 
0.4%
Other values (186) 186
76.5%
2023-12-12T21:10:35.892744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 134
 
8.5%
인 127
 
8.1%
노 126
 
8.0%
학 121
 
7.7%
84
 
5.4%
회 53
 
3.4%
교 53
 
3.4%
실 51
 
3.2%
지 45
 
2.9%
부 41
 
2.6%
Other values (177) 735
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1474
93.9%
Space Separator 84
 
5.4%
Open Punctuation 5
 
0.3%
Close Punctuation 5
 
0.3%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 134
 
9.1%
인 127
 
8.6%
노 126
 
8.5%
학 121
 
8.2%
회 53
 
3.6%
교 53
 
3.6%
실 51
 
3.5%
지 45
 
3.1%
부 41
 
2.8%
사 37
 
2.5%
Other values (172) 686
46.5%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
4 1
50.0%
Space Separator
ValueCountFrequency (%)
84
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1474
93.9%
Common 96
 
6.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 134
 
9.1%
인 127
 
8.6%
노 126
 
8.5%
학 121
 
8.2%
회 53
 
3.6%
교 53
 
3.6%
실 51
 
3.5%
지 45
 
3.1%
부 41
 
2.8%
사 37
 
2.5%
Other values (172) 686
46.5%
Common
ValueCountFrequency (%)
84
87.5%
( 5
 
5.2%
) 5
 
5.2%
2 1
 
1.0%
4 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1474
93.9%
ASCII 96
 
6.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 134
 
9.1%
인 127
 
8.6%
노 126
 
8.5%
학 121
 
8.2%
회 53
 
3.6%
교 53
 
3.6%
실 51
 
3.5%
지 45
 
3.1%
부 41
 
2.8%
사 37
 
2.5%
Other values (172) 686
46.5%
ASCII
ValueCountFrequency (%)
84
87.5%
( 5
 
5.2%
) 5
 
5.2%
2 1
 
1.0%
4 1
 
1.0%

도로명주소
Text

UNIQUE 

Distinct159
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-12T21:10:36.221246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length24.333333
Min length15

Characters and Unicode

Total characters3869
Distinct characters175
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)100.0%

Sample

1st row부산광역시 중구 대청로99번길 22
2nd row부산광역시 서구 대티로 129-5
3rd row부산광역시 서구 구덕로 186번길 9
4th row부산광역시 서구 망양로 193번길 104
5th row부산광역시 서구 해돋이로 67
ValueCountFrequency (%)
부산광역시 155
23.6%
북구 19
 
2.9%
해운대구 17
 
2.6%
부산진구 16
 
2.4%
금정구 14
 
2.1%
동래구 13
 
2.0%
남구 13
 
2.0%
영도구 12
 
1.8%
연제구 11
 
1.7%
사상구 10
 
1.5%
Other values (329) 376
57.3%
2023-12-12T21:10:36.733392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
502
 
13.0%
산 184
 
4.8%
동 180
 
4.7%
부 177
 
4.6%
구 161
 
4.2%
광 158
 
4.1%
시 158
 
4.1%
역 155
 
4.0%
로 150
 
3.9%
( 144
 
3.7%
Other values (165) 1900
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2449
63.3%
Decimal Number 606
 
15.7%
Space Separator 502
 
13.0%
Open Punctuation 144
 
3.7%
Close Punctuation 143
 
3.7%
Dash Punctuation 21
 
0.5%
Other Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 184
 
7.5%
동 180
 
7.3%
부 177
 
7.2%
구 161
 
6.6%
광 158
 
6.5%
시 158
 
6.5%
역 155
 
6.3%
로 150
 
6.1%
길 95
 
3.9%
번 87
 
3.6%
Other values (150) 944
38.5%
Decimal Number
ValueCountFrequency (%)
1 133
21.9%
2 87
14.4%
3 64
10.6%
4 55
9.1%
5 54
8.9%
9 49
 
8.1%
0 48
 
7.9%
7 47
 
7.8%
6 38
 
6.3%
8 31
 
5.1%
Space Separator
ValueCountFrequency (%)
502
100.0%
Open Punctuation
ValueCountFrequency (%)
( 144
100.0%
Close Punctuation
ValueCountFrequency (%)
) 143
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2449
63.3%
Common 1420
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 184
 
7.5%
동 180
 
7.3%
부 177
 
7.2%
구 161
 
6.6%
광 158
 
6.5%
시 158
 
6.5%
역 155
 
6.3%
로 150
 
6.1%
길 95
 
3.9%
번 87
 
3.6%
Other values (150) 944
38.5%
Common
ValueCountFrequency (%)
502
35.4%
( 144
 
10.1%
) 143
 
10.1%
1 133
 
9.4%
2 87
 
6.1%
3 64
 
4.5%
4 55
 
3.9%
5 54
 
3.8%
9 49
 
3.5%
0 48
 
3.4%
Other values (5) 141
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2449
63.3%
ASCII 1420
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
502
35.4%
( 144
 
10.1%
) 143
 
10.1%
1 133
 
9.4%
2 87
 
6.1%
3 64
 
4.5%
4 55
 
3.9%
5 54
 
3.8%
9 49
 
3.5%
0 48
 
3.4%
Other values (5) 141
 
9.9%
Hangul
ValueCountFrequency (%)
산 184
 
7.5%
동 180
 
7.3%
부 177
 
7.2%
구 161
 
6.6%
광 158
 
6.5%
시 158
 
6.5%
역 155
 
6.3%
로 150
 
6.1%
길 95
 
3.9%
번 87
 
3.6%
Other values (150) 944
38.5%

전화번호
Text

MISSING 

Distinct155
Distinct (%)99.4%
Missing3
Missing (%)1.9%
Memory size1.4 KiB
2023-12-12T21:10:37.005909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1872
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique154 ?
Unique (%)98.7%

Sample

1st row051-247-1820
2nd row051-256-0734
3rd row051-256-2301
4th row051-253-1922
5th row051-248-6321
ValueCountFrequency (%)
051-582-2483 2
 
1.3%
051-264-9033 1
 
0.6%
051-581-4008 1
 
0.6%
051-247-1820 1
 
0.6%
051-543-5717 1
 
0.6%
051-202-8810 1
 
0.6%
051-265-9471 1
 
0.6%
051-205-0708 1
 
0.6%
051-293-2688 1
 
0.6%
051-206-9763 1
 
0.6%
Other values (145) 145
92.9%
2023-12-12T21:10:37.410285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 312
16.7%
5 300
16.0%
1 292
15.6%
0 276
14.7%
3 121
 
6.5%
6 111
 
5.9%
2 109
 
5.8%
4 104
 
5.6%
7 95
 
5.1%
8 80
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1560
83.3%
Dash Punctuation 312
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 300
19.2%
1 292
18.7%
0 276
17.7%
3 121
7.8%
6 111
 
7.1%
2 109
 
7.0%
4 104
 
6.7%
7 95
 
6.1%
8 80
 
5.1%
9 72
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 312
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1872
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 312
16.7%
5 300
16.0%
1 292
15.6%
0 276
14.7%
3 121
 
6.5%
6 111
 
5.9%
2 109
 
5.8%
4 104
 
5.6%
7 95
 
5.1%
8 80
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1872
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 312
16.7%
5 300
16.0%
1 292
15.6%
0 276
14.7%
3 121
 
6.5%
6 111
 
5.9%
2 109
 
5.8%
4 104
 
5.6%
7 95
 
5.1%
8 80
 
4.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct158
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.06048
Minimum128.81701
Maximum129.21329
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T21:10:37.593232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.81701
5-th percentile128.97987
Q1129.01973
median129.06753
Q3129.09807
95-th percentile129.15535
Maximum129.21329
Range0.3962754
Interquartile range (IQR)0.07833785

Descriptive statistics

Standard deviation0.05951051
Coefficient of variation (CV)0.0004611056
Kurtosis1.8715725
Mean129.06048
Median Absolute Deviation (MAD)0.0366714
Skewness-0.6215707
Sum20520.616
Variance0.0035415008
MonotonicityNot monotonic
2023-12-12T21:10:37.785366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8762151 2
 
1.3%
129.031058 1
 
0.6%
128.9805856 1
 
0.6%
128.9600056 1
 
0.6%
128.985473 1
 
0.6%
129.0055561 1
 
0.6%
129.0077021 1
 
0.6%
128.9635537 1
 
0.6%
128.9934067 1
 
0.6%
128.9867137 1
 
0.6%
Other values (148) 148
93.1%
ValueCountFrequency (%)
128.817012 1
0.6%
128.8762151 2
1.3%
128.9028146 1
0.6%
128.9600056 1
0.6%
128.9635537 1
0.6%
128.9727618 1
0.6%
128.9734691 1
0.6%
128.9805856 1
0.6%
128.9832169 1
0.6%
128.9835963 1
0.6%
ValueCountFrequency (%)
129.2132874 1
0.6%
129.1862213 1
0.6%
129.1752248 1
0.6%
129.1731996 1
0.6%
129.1700013 1
0.6%
129.1645481 1
0.6%
129.1625165 1
0.6%
129.1585247 1
0.6%
129.1550004 1
0.6%
129.150092 1
0.6%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct158
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.170642
Minimum35.029833
Maximum35.293396
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T21:10:37.967738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.029833
5-th percentile35.085344
Q135.13139
median35.173577
Q335.21148
95-th percentile35.253148
Maximum35.293396
Range0.26356274
Interquartile range (IQR)0.080089575

Descriptive statistics

Standard deviation0.052947348
Coefficient of variation (CV)0.0015054416
Kurtosis-0.49508978
Mean35.170642
Median Absolute Deviation (MAD)0.03880329
Skewness-0.20593276
Sum5592.1321
Variance0.0028034217
MonotonicityNot monotonic
2023-12-12T21:10:38.133549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.1273856 2
 
1.3%
35.10453177 1
 
0.6%
35.08854547 1
 
0.6%
35.09639944 1
 
0.6%
35.06274344 1
 
0.6%
35.08851194 1
 
0.6%
35.09446142 1
 
0.6%
35.05122843 1
 
0.6%
35.09586857 1
 
0.6%
35.08563822 1
 
0.6%
Other values (148) 148
93.1%
ValueCountFrequency (%)
35.02983289 1
0.6%
35.05122843 1
0.6%
35.06274344 1
0.6%
35.07221265 1
0.6%
35.07600143 1
0.6%
35.08121547 1
0.6%
35.0833273 1
0.6%
35.08517116 1
0.6%
35.08536319 1
0.6%
35.08551797 1
0.6%
ValueCountFrequency (%)
35.29339563 1
0.6%
35.27917441 1
0.6%
35.27355883 1
0.6%
35.26773195 1
0.6%
35.2646556 1
0.6%
35.25988579 1
0.6%
35.2588917 1
0.6%
35.25636309 1
0.6%
35.25279093 1
0.6%
35.25168258 1
0.6%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2023-09-30 00:00:00
Maximum2023-09-30 00:00:00
2023-12-12T21:10:38.273042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:38.414096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T21:10:34.741891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:34.208662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:34.830427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:34.305917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:10:38.478971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구군명경도위도
구군명1.0000.8630.837
경도0.8631.0000.439
위도0.8370.4391.000
2023-12-12T21:10:38.564023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경도위도구군명
경도1.0000.3180.539
위도0.3181.0000.515
구군명0.5390.5151.000

Missing values

2023-12-12T21:10:34.943015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:10:35.066731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

구군명노인교실명도로명주소전화번호경도위도데이터기준일자
0중구대한노인회 부산중구지회 부설 노인대학부산광역시 중구 대청로99번길 22051-247-1820129.03105835.1045322023-09-30
1서구노인건강학교부산광역시 서구 대티로 129-5051-256-0734129.00948335.1107532023-09-30
2서구소문노인대학부산광역시 서구 구덕로 186번길 9051-256-2301129.02024935.1014862023-09-30
3서구한마음노인대학부산광역시 서구 망양로 193번길 104051-253-1922129.02635935.1111792023-09-30
4서구해강노인교실부산광역시 서구 해돋이로 67051-248-6321129.02023235.0851712023-09-30
5동구범일노인대학(장기휴지)부산광역시 동구 범곡로 9(범일동)051-646-5979129.05573235.138872023-09-30
6동구인창실버예술대학부산광역시 동구 고관로 36(초량동)051-714-3872129.04305735.1225562023-09-30
7동구비둘기노인대학부산광역시 동구 성남로 37(좌천동)051-635-5734129.05408935.1298072023-09-30
8동구자성대노인복지관 노인교실부산광역시 동구 자성로 140번길 32(범일동051-632-7597129.06484135.1356442023-09-30
9동구동구종합사회복지관 오색빛깔실버대학부산광역시 동구 안창로57(범일동)051-633-3367129.0424335.1456282023-09-30
구군명노인교실명도로명주소전화번호경도위도데이터기준일자
149사상구사상구종합사회복지관 다솜노인대학부산광역시 사상구 백양대로 527(모라동)051-314-8948128.99477935.1554312023-09-30
150사상구백양복지관부설노인교실부산광역시 사상구 모라로192번길 20-23(모라동)051-305-4286129.00184335.1827572023-09-30
151사상구대한노인회사상구지회 부설 노인대학부산광역시 사상구 사상로319번길 6 (덕포동)051-304-2160128.98362735.1735772023-09-30
152사상구학장종합사회복지관 천수어르신교실부산광역시 사상구 학감대로49번길 28-70(학장동)051-311-4017128.98974635.1386522023-09-30
153사상구모라교회부설 모라상록교실부산광역시 사상구 모덕로95번길 101 (모라동)051-302-9191128.98748535.1857422023-09-30
154사상구감전교회부설 감전어르신 교실부산광역시 사상구 괘감로 77(괘법동)051-325-9341128.98321735.158692023-09-30
155사상구은혜로교회노인대학(구엄궁교회)부산광역시 사상구 엄궁로203번길 17 (엄궁동)051-313-4603128.97276235.1296412023-09-30
156사상구사상노인대학부산광역시 사상구 새벽로 172 (감전동)051-311-7587128.98359635.1564692023-09-30
157기장군철마노인대학부산광역시 기장군 철마면 개좌로 822051-721-9136129.15009235.2735592023-09-30
158기장군기장군지회 부설 노인대학부산광역시 기장군 기장읍 차성로333번길 4051-722-5610129.21328735.2474862023-09-30